Machine learning (ML) models are often based on complex black-box architectures that are difficult to interpret. This interpretability problem can hinder the use of ML in fields like medicine, ecology, and insurance, and has boosted research in interpretable machine learning (IML). Here, we propose a novel approach for the functional decomposition of black-box predictions, which is a core concept of IML. This approach replaces the prediction function with a surrogate model consisting of simpler subfunctions, providing insights into the direction and strength of the main feature contributions and their interactions. Our method is based on a concept termed “stacked orthogonality”, which ensures that the main effects capture as much functional behavior as possible. To compute the subfunctions, we combine neural additive modeling with an efficient post-hoc orthogonalization procedure. Our method yielded plausible results in an analysis of stream biological condition in the Chesapeake Bay watershed (United States).
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Serology data indicated transmission of SARS-CoV-2 and persistence during the seven-month sampling period. Traditional disease modelling based on deer-to-deer transmission indicated relatively low prevalence with an R0 of 1.9 and recovery period of 7 days; however, individual-based modelling informed by GPS tracked-movement data captured a potential transmission event. Phylogenetic analyses revealed a recurring pattern of divergent groups of deer-derived sequences with human-derived sequences falling close to each deer-derived cluster. Further, human-derived sequences were frequently sampled months prior to the deer-derived sequences, indicating repeated human to deer spillover. Using multiple types of data as well as both fine and broad scale analyses, we have characterized a pattern of localized outbreaks of SARS-CoV-2 within white-tailed deer populations that are likely recurring due to frequent spillover events. Our results suggest that while deer-to-deer transmission occurs over small spatiotemporal scales, SARS-CoV-2 persistence over longer periods and across larger regions is likely driven by repeated spillover from human populations.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rsbl.2025.0540","usgsCitation":"Giglio, R.M., Westmoreland, A., Wilber, M.Q., WIlson-Henjum, G., Chan, A.N., Gardner, B., Horpiencharoen, W., Gagne, R.B., Corondi, A., Baker, A., Combs, M., Chandler, J., Manlove, K., Pepin, K.M., and Walter, W., 2025, Viral outbreak dynamics and evolution in wildlife at the interface with humans: Biology Letters, v. 21, no. 12, 20250540, 7 p., https://doi.org/10.1098/rsbl.2025.0540.","productDescription":"20250540, 7 p.","ipdsId":"IP-182184","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":498936,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsbl.2025.0540","text":"Publisher Index Page"},{"id":498836,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Clearfield 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These decisions involve altering the timing and magnitude of water releases from dams and reservoirs, which can affect habitats for economically important and Federally and State-listed endangered fish species, water deliveries for agriculture or municipalities, and water quality. In this report, we describe the results of a rapid structured decision-making process used to assist management agencies in evaluating tradeoffs while gathering input from cooperating agencies, rightsholders, or interested parties (hereafter participants) through facilitated workshops in spring 2025. Consideration of alternative water management actions was initiated by the continued decline of Hypomesus transpacificus (delta smelt) populations and the issuance of a new biological opinion for the CVP and SWP long-term operations on the effects on delta smelt and other Endangered Species Act-listed species in November 2024. An Executive Order was also issued in January 2025, directing the Bureau of Reclamation to maximize water deliveries. Participants, led by the U.S. Geological Survey and cooperating agencies, identified 8 fundamental values (hereafter objectives) and 11 alternative water management scenarios (or “alternative management actions” based on the PrOACT model). Using multicriteria decision analysis, we evaluated performance (or “consequences” based on a consequence table analysis) and analyzed tradeoffs of alternative water management actions to the fundamental objectives. We ranked the alternative water management actions based on four participants’ objective weights and composite utility scores calculated using a linear value function. The three highest ranking alternative water management actions had the poorest performance for delta smelt but performed best for CVP and SWP water exports and objectives related to coldwater pool operations for salmonids. An optimum strategy that could prevent the extinction of delta smelt was not determined for this study. However, insights gained from our rapid decision analysis suggested nonflow scenarios could benefit the delta smelt population, including in drier years, and could be considered to avoid curtailment of water exports.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251055","collaboration":"Prepared in cooperation with the U.S. Bureau of Reclamation, the Metropolitan Water District of Southern California, and the California Department of Water Resources","usgsCitation":"Healy, B.D., Phillis, C.C., Mahardja, B., Koizumi, C., Pien, C., Parker, N., Conrad, J.L., Ekstrom, J., Leimbach, J., Silberblatt, R., Fischer, T., and Ehlo, C., 2025, Rapid structured decision making for Hypomesus transpacificus (delta smelt) summer–fall freshwater outflow management: U.S. Geological Survey Open-File Report 2025–1055, 36 p., https://doi.org/10.3133/ofr20251055.","productDescription":"Report: viii, 36 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-179521","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":497241,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1055/ofr20251055.pdf","size":"1.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1055 PDF"},{"id":497240,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1055/coverthb.jpg"},{"id":497244,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1055/images/"},{"id":497245,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13BBC7D","text":"USGS data release","linkHelpText":"Multicriteria decision analysis scores for rapid delta smelt decision analysis"},{"id":497242,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251055/full","description":"OFR 2025-1055 HTML"},{"id":497243,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1055/ofr20251055.XML","description":"OFR 2025-1055 XML"}],"contact":"Director, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
Decisions on how to store and distribute water in California’s Central Valley are made considering the use of water resources by people, fish and wildlife, and the effects on water quality. Water is stored behind dams throughout the Central Valley for later release into rivers and canals for distribution to meet different water needs. Declining water availability and increasing human demands for water over recent decades have made these decisions increasingly difficult, especially because different uses of water resources often conflict. This report summarizes a facilitated decision-making process, led by the U.S. Geological Survey, involving water, fish, wildlife managers, and those that have an interest in how water is used (interest holders) in the Central Valley. This process provides information for water managers to consider when deciding how to distribute water resources to meet the needs for endangered Hypomesus transpacificus (delta smelt), different runs of Oncorhynchus tshawytscha (Chinook salmon), and Oncorhynchus mykiss (Central Valley steelhead), while maximizing water deliveries for human use and maintaining water quality standards.
","publicationDate":"2025-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Healy, Brian D. 0000-0002-4402-638X","orcid":"https://orcid.org/0000-0002-4402-638X","contributorId":304257,"corporation":false,"usgs":true,"family":"Healy","given":"Brian","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":951768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillis, Corey C. 0000-0002-8940-3441","orcid":"https://orcid.org/0000-0002-8940-3441","contributorId":344284,"corporation":false,"usgs":false,"family":"Phillis","given":"Corey","middleInitial":"C.","affiliations":[{"id":82325,"text":"The Metropolitan Water District of Southern California","active":true,"usgs":false}],"preferred":false,"id":951769,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mahardja, Brian 0000-0003-0695-3745","orcid":"https://orcid.org/0000-0003-0695-3745","contributorId":288940,"corporation":false,"usgs":false,"family":"Mahardja","given":"Brian","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":951770,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koizumi, Cameron","contributorId":363551,"corporation":false,"usgs":false,"family":"Koizumi","given":"Cameron","affiliations":[{"id":86721,"text":"US Bureau of Reclamation, Bay-Delta Office, Sacramento, California","active":true,"usgs":false}],"preferred":false,"id":951771,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pien, Catarina","contributorId":297193,"corporation":false,"usgs":false,"family":"Pien","given":"Catarina","email":"","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":951772,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parker, Nancy","contributorId":363552,"corporation":false,"usgs":false,"family":"Parker","given":"Nancy","affiliations":[{"id":86721,"text":"US Bureau of Reclamation, Bay-Delta Office, Sacramento, California","active":true,"usgs":false}],"preferred":false,"id":951773,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conrad, J. 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These dynamics are shaped by both ecological factors, like interaction strength, and anthropogenic factors, like harvest intensity, which can have large-scale implications for community structure. However, few studies have focused on the combined impact of these effects and their contribution to phenomena like prey release within two-species frameworks. In this study, we investigate the interactive impact of interaction strength and harvest pressure on two trophic levels in a predator–prey system using a mathematical modeling approach. Our results reveal that interaction strength plays a crucial role in shaping population dynamics, with high interaction strength leading to a predator-dominated system and low interaction strength enabling coexistence between species. The addition of predator harvest into the system reveals complex and counterintuitive behavior not seen in unharvested systems, likely due to the destabilizing impacts of harvest at some interaction strengths. Specifically, the inclusion of harvest on the predator can induce a range of behaviors, such as prey release and predator decline, that alter the equilibrium abundance of both predator and prey populations. Interestingly, predator–prey systems with intermediate to high interaction strengths achieve maximum total abundance with low harvest levels rather than in scenarios with no harvest pressure, as prey populations benefit greatly from reduced predation mortality associated with predator harvest. We gain insights into the complex interplay between predator–prey interactions and human activities in shaping community composition and abundances across trophic levels. This study provides potential mechanisms that may explain the observed variation in numerical prey release in trophically complex systems in which predators and prey are both extracted, like coral reef fisheries. Results highlight the need for resource management to consider the wide range of factors that shape ecosystem dynamics to develop effective strategies that safeguard the long-term health of complex ecosystems and the human communities that they support.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70449","usgsCitation":"Rahnke, S.A., Winter. Kawika B., Raz, L., McManus, L.C., 2025, Interaction strength and harvest intensity mediate predator–prey dynamics on coral reefs: Ecosphere, v. 16, no. 12, e70449, 15 p., https://doi.org/10.1002/ecs2.70449.","productDescription":"e70449, 15 p.","ipdsId":"IP-168169","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":500593,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70449","text":"Publisher Index Page"},{"id":500430,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Rahnke, Sophia A.","contributorId":366825,"corporation":false,"usgs":false,"family":"Rahnke","given":"Sophia","middleInitial":"A.","affiliations":[{"id":64253,"text":"University of Hawaiʻi at Mānoa","active":true,"usgs":false}],"preferred":false,"id":956278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winter. Kawika B.","contributorId":366826,"corporation":false,"usgs":false,"family":"Winter. Kawika B.","affiliations":[{"id":64253,"text":"University of Hawaiʻi at Mānoa","active":true,"usgs":false}],"preferred":false,"id":956279,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Raz, Lillian Joy Tuttle 0000-0002-5009-8080","orcid":"https://orcid.org/0000-0002-5009-8080","contributorId":354940,"corporation":false,"usgs":true,"family":"Raz","given":"Lillian Joy Tuttle","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McManus, Lisa C.","contributorId":366827,"corporation":false,"usgs":false,"family":"McManus","given":"Lisa","middleInitial":"C.","affiliations":[{"id":64253,"text":"University of Hawaiʻi at Mānoa","active":true,"usgs":false}],"preferred":false,"id":956281,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273281,"text":"70273281 - 2025 - Spatial connections between the timing of hydroclimatic extremes","interactions":[],"lastModifiedDate":"2025-12-30T17:01:25.636767","indexId":"70273281","displayToPublicDate":"2025-12-09T10:59:12","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17124,"text":"Nature Water","active":true,"publicationSubtype":{"id":10}},"title":"Spatial connections between the timing of hydroclimatic extremes","docAbstract":"No abstract available.
","language":"English","publisher":"Nature","doi":"10.1038/s44221-025-00536-2","usgsCitation":"Archfield, S., 2025, Spatial connections between the timing of hydroclimatic extremes: Nature Water, v. 3, p. 1352-1353, https://doi.org/10.1038/s44221-025-00536-2.","productDescription":"2 p.","startPage":"1352","endPage":"1353","ipdsId":"IP-182869","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":498157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2025-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Archfield, Stacey 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":214835,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":953017,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70272699,"text":"sir20255086 - 2025 - Conceptual and numerical groundwater flow model of the Iowa River alluvial aquifer near Tama County, Iowa, 1980 through 2022","interactions":[],"lastModifiedDate":"2026-02-03T16:48:21.047788","indexId":"sir20255086","displayToPublicDate":"2025-12-08T13:13:22","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5086","displayTitle":"Conceptual and Numerical Groundwater Flow Model of the Iowa River Alluvial Aquifer near Tama County, Iowa, 1980 through 2022","title":"Conceptual and numerical groundwater flow model of the Iowa River alluvial aquifer near Tama County, Iowa, 1980 through 2022","docAbstract":"The Iowa River alluvial aquifer is an important source of water on the Meskwaki Settlement in Tama County, Iowa, which is land owned by the Sac & Fox Tribe of the Mississippi in Iowa (commonly known as the Meskwaki Nation). The U.S. Geological Survey constructed a groundwater flow model, including a conceptual and numerical model, of the Iowa River alluvial aquifer and underlying hydrogeologic units near the Meskwaki Settlement in Tama County, Iowa, for the period of January 1980–August 2022 to estimate the fraction of water pumped from the Iowa River alluvial aquifer by Meskwaki Settlement wells that is derived from streamflow depletion in the Iowa River and its tributaries. Streamflow depletion is a reduction in streamflow caused by groundwater pumping and includes the interception by groundwater production wells of water that otherwise would have been discharged to streams (called “captured groundwater discharge”) and induced infiltration of streamflow to the production wells. Calibrated model runs were performed with no simulated pumping and simulated pumping only at Meskwaki Settlement wells, and the change in simulated flow rates between the groundwater system and streams for the two model runs represents the amount of streamflow depletion in the Iowa River and tributary streams resulting from pumping at the Meskwaki Settlement wells. Streamflow depletion in the Iowa River and its tributaries as a percentage of simulated pumping at the Meskwaki Settlement wells was calculated by dividing this difference by the total simulated pumping rate for the Meskwaki Settlement wells. The model results demonstrate that the mean monthly streamflow depletion, including induced infiltration and captured discharge, in the Iowa River and its tributary streams as a percentage of mean monthly pumping at the Meskwaki Settlement wells was 97.4 percent and ranged from 65.4 to 112 percent. Of the total streamflow depletion, mean monthly induced recharge was 20.9 percent and ranged from 4.9 to 37.2 percent. Mean monthly captured discharge was 76.5 percent and ranged from 57.1 to 97.1 percent. These results indicate that most of the water pumped from the Meskwaki Settlement wells is the result of streamflow depletion, in the form of both induced infiltration and captured discharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255086","collaboration":"Prepared in cooperation with the Sac & Fox Tribe of the Mississippi in Iowa","usgsCitation":"Goldstein, K.M.F., and Davis, K.W., 2025, Conceptual and numerical groundwater flow model of the Iowa River alluvial aquifer near Tama County, Iowa, 1980 through 2022: U.S. Geological Survey Scientific Investigations Report 2025–5086, 55 p., https://doi.org/10.3133/sir20255086.","productDescription":"Report: viii, 55 p.; Data Release; Dataset","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154245","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497068,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5086/coverthb.jpg"},{"id":497069,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5086/sir20255086.pdf","text":"Report","size":"20.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5086"},{"id":497070,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5086/sir20255086.XML"},{"id":497071,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5086/images/"},{"id":497074,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":497073,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1CPXXGM","text":"USGS data release","linkHelpText":"MODFLOW 6 groundwater flow model for the Iowa River alluvial aquifer near Tama, Iowa, 1980 through 2022"},{"id":497072,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255086/full"},{"id":497812,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119054.htm"}],"country":"United States","state":"Iowa","county":"Tama County","otherGeospatial":"Iowa River alluvial aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.86911713753273,\n 42.130588756475845\n ],\n [\n -92.86911713753273,\n 41.830673568326176\n ],\n [\n -92.25633472266213,\n 41.830673568326176\n ],\n [\n -92.25633472266213,\n 42.130588756475845\n ],\n [\n -92.86911713753273,\n 42.130588756475845\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
Miami-Dade County is part of a densely populated urban corridor in southeastern Florida. The Biscayne aquifer serves as Miami-Dade County’s primary drinking water source and is characterized by highly permeable karstic limestone and carbonate sand. The aquifer’s coastal location and permeable nature make it susceptible to saltwater intrusion. Monitoring the current inland extent and the rate of movement of the saltwater front in the aquifer can inform management strategies for conserving the long-term sustainability of the county’s water supply. In the 1950s, the U.S. Geological Survey published a map of the inland extent of saltwater intrusion in the Biscayne aquifer and has continued to update this map to monitor changes over time, with the most recent update published in 2018. An updated map has been created showing the approximate inland extent of saltwater intrusion in the Biscayne aquifer in eastern Miami-Dade County in 2022, with the 2018 extent shown for comparison. The inland extent of saltwater intrusion was mapped through the interpretation of borehole electromagnetic induction logs and measurements of chloride and specific conductance in groundwater samples. The location of the saltwater interface at the base of the Biscayne aquifer was represented by the 1,000-milligram-per-liter isochlor. This report describes changes in the location of the saltwater interface from 2018 to 2022. By 2022, the saltwater interface had moved farther inland in both the northern and southern parts of the county, advancing by as much as 0.3 kilometer in the north and up to 0.8 kilometer in the Model Land Area to the south. However, it remained relatively unchanged from its 2018 position in the east-central part of the county.
Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
7595 SW 33d St.
Davie, FL 33314
Contact Us- USGS Publications Warehouse
","tableOfContents":"The U.S. Geological Survey is developing nationally consistent water-use modeling approaches to replace previous methods relying on locally specific reported and estimated data. These national assessments require datasets that incorporate water withdrawal variability across the United States and over long periods. However, source data often have unclear definitions, missing or varied units, differing temporal resolutions, varied data quality, and inconsistent formats, which hinder automation and require individualized processing. The public-supply datasets described in this paper were used in machine learning models to estimate annual and monthly public-supply water use for 2000–2020 for the conterminous United States (CONUS) and in a model to estimate public-supply deliveries. Public-supply withdrawal data were acquired for the CONUS and the District of Columbia; however, 11 states had annual data for only 1 year, and 10 states had no monthly data. Annual withdrawal data were acquired for 81% of public-supply water service areas, and monthly withdrawal data were acquired for 47% for at least 1 year from 2000 to 2020. These datasets and methods provide the most comprehensive collection of reported public-supply withdrawals to date and can be used by water-use managers, the scientific community, and the broader public. The extensive data processing described herein can be applicable to datasets representing other categories of water use.
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,{"id":70273138,"text":"70273138 - 2025 - Rice cultivation supports growth and survival of a threatened semi-aquatic reptile","interactions":[],"lastModifiedDate":"2025-12-16T16:18:00.57795","indexId":"70273138","displayToPublicDate":"2025-12-08T10:06:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Rice cultivation supports growth and survival of a threatened semi-aquatic reptile","docAbstract":"Integration of agroecosystems and other working landscapes with protected lands and waters is critical to the conservation of Earth's biodiversity. Rice agroecosystems support many species by providing aquatic habitat where natural wetlands have been altered or drained. In regions with long dry seasons, rice fields and associated irrigation canals provide essential habitat for wetland-dependent species. We quantified the spatial scale and magnitude of the effect of rice growing on the growth and survival of the giant gartersnake (Thamnophis gigas), a threatened species that persists primarily in areas of rice agriculture in the Central Valley of California, USA. We used structural causal models to identify drought condition as a key confounder to adjust for when estimating the total effect of rice growing on demographic rates. We analyzed capture-mark-recapture data from 19 populations of giant gartersnakes with an integrated growth–survival model and used distance-weighted covariates to account for the decline in influence of rice with increasing distance from our study sites. We found strong support for a positive effect of rice grown within 1.9 km of a canal on giant gartersnake growth. There was also support for a positive effect of rice on giant gartersnake survival, although the spatial scale extended out to 5 km or more. Our results demonstrate how active rice growing benefits giant gartersnakes inhabiting irrigation canals and demonstrate an approach for studying landscape effects on wildlife in agroecosystems.
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S.M.","contributorId":364269,"corporation":false,"usgs":false,"family":"Ersan","given":"Julia","middleInitial":"S.M.","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":952425,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fulton, Alexandria M.","contributorId":364271,"corporation":false,"usgs":false,"family":"Fulton","given":"Alexandria","middleInitial":"M.","affiliations":[{"id":86778,"text":"Fish Program WADFW (former USGS)","active":true,"usgs":false}],"preferred":false,"id":952426,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":215986,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian","email":"bhalstead@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research 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The units of ρdry have not been consistently reported in the literature, leading to confusion, particularly in the calculation of sediment budgets that typically require integrating mass-based and volumetric components. Relationships between ρdry and sediment composition have been developed for multiple regions and differ between systems. Developing a system-specific predictive model for ρdry can help fill data gaps and improve sediment budgets, model accuracy, and estimates of quantities of sediment needed for restoration. In this study, we investigate whether ρdry in San Francisco Estuary can be predicted from organic carbon content or percent of fines, which are more easily or frequently measured than ρdry. We compiled sediment properties from samples collected over the past decade throughout the intertidal and subtidal regions of San Francisco Bay and the Sacramento–San Joaquin Delta to examine this relationship. Sample composition ranged from 2.18 to 99.97% fines (particles < 0.0625 mm), ρ-dry ranged from 0.22 to 1.60 g cm-3, and organic carbon ranged from 0.06 to 7.98%. Regression analysis indicates that the percent of fines explains 93% of the variation of ρ-dry (p-value < 0.05, N = 81). The coefficient of determination decreased by ~1% when organic carbon was incorporated in the regression analysis. Comparison of this predictive ρ-dry model to four published models based on samples from other regions supports previous findings that the relationship between ρdry and grain size may vary by system. We also examined additional factors that may affect sediment erodibility, such as hydrographic and oceanographic conditions. Classification of sample sites as intertidal vs. subtidal or wavy vs. non-wavy each significantly explained the residuals from the ρdry model, and both intertidal and wavy conditions were associated with higher ρ-dry values.
","language":"English","publisher":"University of California Davis","doi":"10.15447/sfews.2025v23iss4art6","usgsCitation":"McGill, S., and Lacy, J.R., 2025, Predicting sediment bulk density for San Francisco Estuary: San Francisco Estuary and Watershed Science, v. 23, no. 4, 6, 21 p., https://doi.org/10.15447/sfews.2025v23iss4art6.","productDescription":"6, 21 p.","ipdsId":"IP-177286","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":498039,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2025v23iss4art6","text":"Publisher Index Page"},{"id":497767,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.5,\n 38.4\n ],\n [\n -122.8,\n 38.4\n ],\n [\n -122.8,\n 37.4\n ],\n [\n -121.5,\n 37.4\n ],\n [\n -121.5,\n 38.4\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"McGill, Samantha C. 0000-0001-9320-8764","orcid":"https://orcid.org/0000-0001-9320-8764","contributorId":304095,"corporation":false,"usgs":true,"family":"McGill","given":"Samantha C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":952710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lacy, Jessica R. 0000-0002-2797-6172","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":201703,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":952711,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70273298,"text":"70273298 - 2025 - Causal analysis of fire regime drivers in California","interactions":[],"lastModifiedDate":"2026-01-05T14:54:53.160898","indexId":"70273298","displayToPublicDate":"2025-12-08T08:51:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Causal analysis of fire regime drivers in California","docAbstract":"Understanding the relative contribution of climate and human factors to wildfires is critical for managing risk across California’s diverse ecosystems, in the United States (US).
We propose a model that distinguishes between proximate and ultimate drivers of fire regimes and apply it to a century of fire and climate data to assess regional variation in causal mechanisms.
We analyzed fire statistics (1910–2021) alongside climate and weather data, stratifying the state by 10 ecoregions.
Northern forests had the strongest correlation with the proximate factor fuel aridity, ultimately due to climate. Fire rotation intervals exceeded 100 years, implicating woody fuel accumulation as an additional factor. Lightning ignitions occurred in decadal bursts, with dense strike events potentially overwhelming fire-fighting resources. Lower elevation/latitude foothill ecoregions experienced highest fire activity following wet winters and springs, implicating control by herbaceous fuel loads and a negative effect of global warming on future fires. Human ignitions dominate in these ecoregions, and population growth contributes to expansion of powerlines, a major ignition source.
While climate change may increase fire activity in forested ecoregions, its role is less pronounced in non-forested ecoregions, where human ignition sources are the dominant factor.
Different areas within ecoregions may require different management actions that reflect the specific proximate and ultimate factors at play.
","language":"English","publisher":"CSIRO","doi":"10.1071/WF25166","usgsCitation":"Keeley, J., and Syphard, A.D., 2025, Causal analysis of fire regime drivers in California: International Journal of Wildland Fire, v. 34, no. 12, WF25166, 27 p., https://doi.org/10.1071/WF25166.","productDescription":"WF25166, 27 p.","ipdsId":"IP-166632","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":498315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"34","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-10-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Keeley, Jon 0000-0002-4564-6521","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":216485,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Syphard, Alexandra D.","contributorId":364829,"corporation":false,"usgs":false,"family":"Syphard","given":"Alexandra","middleInitial":"D.","affiliations":[{"id":38279,"text":"Conservation Biology Institute","active":true,"usgs":false}],"preferred":false,"id":953273,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70273192,"text":"70273192 - 2025 - Biologging to identify nesting and non-nesting emergences for four species of imperiled sea turtles","interactions":[],"lastModifiedDate":"2025-12-18T16:22:12.492162","indexId":"70273192","displayToPublicDate":"2025-12-05T10:12:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Biologging to identify nesting and non-nesting emergences for four species of imperiled sea turtles","docAbstract":"Quantifying sea turtle nesting behavior is essential for recovery planning and evaluating management actions. Traditional monitoring approaches, based on nest counts from beach surveys, can misclassify non-nesting emergences, obscure true fecundity, and underestimate clutch frequency, metrics that directly influence population models and regulatory decisions. Here, we demonstrate that high-resolution acceleration data loggers (ADLs) can reliably discriminate nesting from non-nesting emergences across four imperiled species of sea turtles at sites in the Gulf of America, southeast USA, and Caribbean. From 60 recovered ADL deployments on green (Chelonia mydas; N = 10), hawksbill (Eretmochelys imbricata; N = 7), Kemp’s ridley (Lepidochelys kempii; N = 21), and loggerhead sea turtles (Caretta caretta; N = 22) lasting on average 17.5 ± 8.7 days (range 2–43 days), we identified 54 nesting events and 76 non-nesting emergences, with >97% accuracy when compared to direct observations. These data provide the first observer-validated, species-specific behavioral signatures of nesting phases and reveal correlations between egg-laying duration and clutch size. All non-nesting emergences occurred within 72 hours of subsequent nesting, allowing managers to anticipate nest deposition windows. By refining inter-nesting intervals and fecundity estimates, ADLs offer a practical path to reduce error in clutch frequency estimates. The integration of ADL-derived algorithms with satellite-transmitting tags would enable the remote, real-time monitoring of nesting activity, creating a system for the remote monitoring of inter-nesting intervals and nest fecundity that are crucial to quantify the impacts of climate change and other threats to sea turtle nesting habitat.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2025.1691053","usgsCitation":"Hart, K., White, C.F., Shaver, D.J., Lamont, M., Cherkiss, M., Crowder, A.G., and Whitney, N.M., 2025, Biologging to identify nesting and non-nesting emergences for four species of imperiled sea turtles: Frontiers in Marine Science, v. 12, 1691053, 15 p., https://doi.org/10.3389/fmars.2025.1691053.","productDescription":"1691053, 15 p.","ipdsId":"IP-178699","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":497743,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2025.1691053","text":"Publisher Index Page"},{"id":497677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, North Carolina, Texas","otherGeospatial":"Bald Head Island, Bon Secour National Wildlife Refuge, Buck Island Reef National Monument, Dry Tortugas National Park, Padre Island National Seashore, St. Croix, T.H. Stone Memorial St. Joseph Peninsula State Park, U.S. Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -100,\n 35\n ],\n [\n -100,\n 17\n ],\n [\n -60,\n 17\n ],\n [\n -60,\n 35\n ],\n [\n -100,\n 35\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2025-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":218455,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":952675,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Connor F.","contributorId":364459,"corporation":false,"usgs":false,"family":"White","given":"Connor","middleInitial":"F.","affiliations":[{"id":37373,"text":"New England Aquarium","active":true,"usgs":false}],"preferred":false,"id":952676,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaver, Donna J.","contributorId":364462,"corporation":false,"usgs":false,"family":"Shaver","given":"Donna","middleInitial":"J.","affiliations":[{"id":86822,"text":"National Park Service, Padre Island National Seashore","active":true,"usgs":false}],"preferred":false,"id":952677,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":206258,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":952678,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cherkiss, Michael 0000-0002-7802-6791","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":218466,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":952679,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crowder, Andrew G.","contributorId":364463,"corporation":false,"usgs":false,"family":"Crowder","given":"Andrew","middleInitial":"G.","affiliations":[{"id":86825,"text":"Presently: Xylem","active":true,"usgs":false}],"preferred":false,"id":952680,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Whitney, Nicholas M.","contributorId":364464,"corporation":false,"usgs":false,"family":"Whitney","given":"Nicholas","middleInitial":"M.","affiliations":[{"id":37373,"text":"New England Aquarium","active":true,"usgs":false}],"preferred":false,"id":952681,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273790,"text":"70273790 - 2025 - Wetland hydrologic dynamics and duck productivity are declining in the Prairie Pothole Region, and they are linked","interactions":[],"lastModifiedDate":"2026-01-30T16:40:16.608338","indexId":"70273790","displayToPublicDate":"2025-12-05T09:34:02","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22149,"text":"Environmental and Sustainability Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Wetland hydrologic dynamics and duck productivity are declining in the Prairie Pothole Region, and they are linked","docAbstract":"The Prairie Pothole Region (PPR) of North America is a globally important area hosting >50 % of North America’s breeding ducks. Ducks in the PPR depend on wetlands and grasslands which have experienced accelerated losses in extent and quality due to agriculture. While other bird populations have declined, duck abundance reached record highs recently (2013–2017). We explored this discontinuity by examining monitoring data for trends in pond numbers (wetlands with ponded water) and interannual dynamics (water-level dynamics indexed by interannual change in pond numbers) and how those factors influenced duck productivity in the PPR during 1976–2019. Over time, pond numbers increased but their interannual dynamics declined, indicating stabilization of an ecosystem evolved with a dynamic climate. Our models accounted for 67 and 71 % of variation in productivity of PPR-obligate gadwall (Mareca strepera) and redheads (Aythya americana), respectively. Breeding productivity of these sentinel species was positively correlated with pond abundance and dynamics, and systematically declined. Accordingly, our analyses revealed sensitivity of breeding ducks to systematic change in the PPR previously obscured by increasingly abundant pond numbers. Interannual pond dynamics improved duck productivity and pond dynamics have declined indicating a de facto 44-year decline in duck productivity which is likely driven by water-level stabilization decreasing quality of brood-rearing wetlands. Residual temporal effects indicated that productivity has also declined for other reasons, such as agricultural land use changes. While mechanisms behind these correlations are speculative, they demonstrate the importance of further understanding land use and climate changes in the PPR for conservation of these important species and ecosystems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.indic.2025.101073","usgsCitation":"Anteau, M.J., Szymanski, M.L., and Pearse, A.T., 2025, Wetland hydrologic dynamics and duck productivity are declining in the Prairie Pothole Region, and they are linked: Environmental and Sustainability Indicators, v. 29, 101073, 11 p., https://doi.org/10.1016/j.indic.2025.101073.","productDescription":"101073, 11 p.","ipdsId":"IP-172342","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":499615,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.indic.2025.101073","text":"Publisher Index Page"},{"id":499373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alberta, Iowa, Manitoba, Minnesota, Montana, North Dakota, South Dakota","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.35951256057884,\n 55.830201295287566\n ],\n [\n -115.58338333574763,\n 47.847886890172305\n ],\n [\n -101.7900722437109,\n 47.49234945376459\n ],\n [\n -100.95405193901554,\n 43.77396787878899\n ],\n [\n -96.57786404894601,\n 43.798830626316516\n ],\n [\n -94.52621944089687,\n 42.26192084940283\n ],\n [\n -95.45523589381337,\n 46.222540001545326\n ],\n [\n -97.03293587652475,\n 51.31009651298103\n ],\n [\n -119.35951256057884,\n 55.830201295287566\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":954798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Szymanski, Michael L","contributorId":365789,"corporation":false,"usgs":false,"family":"Szymanski","given":"Michael","middleInitial":"L","affiliations":[{"id":87220,"text":"North Dakota Game and Fish Dept.","active":true,"usgs":false}],"preferred":false,"id":954799,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":954800,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273235,"text":"70273235 - 2025 - Designs for cyanobacterial harmful algal bloom monitoring in the Sacramento–San Joaquin Delta, California","interactions":[],"lastModifiedDate":"2025-12-22T15:16:10.010119","indexId":"70273235","displayToPublicDate":"2025-12-05T08:48:02","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19891,"text":"ESS Open Archive","active":true,"publicationSubtype":{"id":32}},"title":"Designs for cyanobacterial harmful algal bloom monitoring in the Sacramento–San Joaquin Delta, California","docAbstract":"Environments can shape the occurrence and extent of disease outbreaks in wildlife. We studied the effects of environmental features on the occurrence of treponeme-associated hoof disease (TAHD), an emerging infectious disease of free-ranging elk (Cervus canadensis), in southwestern Washington, USA. During the 2016–2022 harvest seasons, successful elk hunters returned mandatory harvest reports and noted the presence or absence of hoof abnormalities indicative of TAHD. We used generalized linear models and an information-theoretic approach to model selection to relate (1) the spatial distribution of hoof abnormalities to features of landscapes (land cover, topography, and soil characteristics) and (2) the temporal distribution of hoof abnormalities to precipitation during the year preceding the harvest season. The probability of hoof disease increased with soil clay content and proportion of agricultural land (88% of model weight). We found no conclusive evidence for an effect of precipitation on the occurrence of TAHD, but this could relate to relatively high annual precipitation (>140 cm) in the study area. Nevertheless, disease cases may have been negatively associated with precipitation during February–June (55% of model weight). Soils and land management practices may increase the risk of hoof disease by promoting the survival of pathogens that cause TAHD, the susceptibility of elk to infection, or the intensity of pathogen transmission among elk when congregated. Focusing on areas where the risk of disease is greatest may facilitate the detection of TAHD during surveillance. Likewise, removing infected elk and dispersing uninfected elk from areas with the greatest risk of disease may enhance the effectiveness of efforts to reduce transmission. Basing this work on the knowledge that disease risk is modified by factors of hosts, pathogens, and environments, this study serves as an application of the epidemiological triad framework to better understand the ecology and epidemiology of an emerging infectious disease in wildlife.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70470","usgsCitation":"Winter, S.N., Sargeant, G., Wild, M.A., Clancey, E., Huyvaert, K.P., Garrison, K., and Fernandez, P., 2025, Land use and soil characteristics are associated with increased risk of treponeme-associated hoof disease in elk: Ecosphere, v. 16, no. 12, e70470, 12 p., https://doi.org/10.1002/ecs2.70470.","productDescription":"e70470, 12 p.","ipdsId":"IP-179906","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":498040,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70470","text":"Publisher Index Page"},{"id":497777,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.5,\n 46.9\n ],\n [\n -123.5,\n 45.9\n ],\n [\n -121.9,\n 45.9\n ],\n [\n -121.9,\n 46.9\n ],\n [\n -123.5,\n 46.9\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Winter, Steven N.","contributorId":362949,"corporation":false,"usgs":false,"family":"Winter","given":"Steven","middleInitial":"N.","affiliations":[{"id":33243,"text":"Washington State University, Pullman, WA","active":true,"usgs":false}],"preferred":false,"id":950860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sargeant, Glen A. 0000-0003-3845-8503","orcid":"https://orcid.org/0000-0003-3845-8503","contributorId":219538,"corporation":false,"usgs":true,"family":"Sargeant","given":"Glen A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":950861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wild, Margaret A.","contributorId":362950,"corporation":false,"usgs":false,"family":"Wild","given":"Margaret","middleInitial":"A.","affiliations":[{"id":33243,"text":"Washington State University, Pullman, WA","active":true,"usgs":false}],"preferred":false,"id":950862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clancey, Erin","contributorId":362951,"corporation":false,"usgs":false,"family":"Clancey","given":"Erin","affiliations":[{"id":33243,"text":"Washington State University, Pullman, WA","active":true,"usgs":false}],"preferred":false,"id":950863,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huyvaert, Kathryn P.","contributorId":362952,"corporation":false,"usgs":false,"family":"Huyvaert","given":"Kathryn","middleInitial":"P.","affiliations":[{"id":33243,"text":"Washington State University, Pullman, WA","active":true,"usgs":false}],"preferred":false,"id":950864,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garrison, Kyle","contributorId":166768,"corporation":false,"usgs":false,"family":"Garrison","given":"Kyle","email":"","affiliations":[],"preferred":false,"id":950865,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fernandez, Pilar","contributorId":362953,"corporation":false,"usgs":false,"family":"Fernandez","given":"Pilar","affiliations":[{"id":33243,"text":"Washington State University, Pullman, WA","active":true,"usgs":false}],"preferred":false,"id":950866,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70272767,"text":"70272767 - 2025 - Foundational principles of an applied cultural evolutionary science for natural resource management and conservation","interactions":[],"lastModifiedDate":"2025-12-08T16:36:25.167321","indexId":"70272767","displayToPublicDate":"2025-12-04T09:28:27","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22143,"text":"Philosophical Transactions of the Royal Society B Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Foundational principles of an applied cultural evolutionary science for natural resource management and conservation","docAbstract":"Culture, as the filter through which people view the world and a key determinant of human behaviour, is central to the practice of natural resource management and conservation. Conservation is intended to moderate the impacts of human cultural modification of the environment, exists as an endeavour because it is culturally valued, and acts largely through policies to encourage or discourage targeted human behaviours. However, culture is not static; as organisms and ecologies evolve, so too does culture exist as a dynamic, interconnected, coevolving element of the social–ecological systems in which management action is situated and implemented. Cultural evolution (CE) offers a valuable theoretical contribution to the scientific understanding of culture, cultural diversity and culture change and has the potential to be harnessed in the applied research and practice of conservation social science. We illustrate the essential principles necessary to grow an applied science of CE for natural resource management and conservation, and identify opportunities for CE to provide valuable information for science-based decision making and help conservation institutions and organizations adapt to the ongoing challenges posed by culture change. This transdisciplinary integration can contribute to improved outcomes across conservation objectives and build more resilient, sustainable social–ecological systems.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rstb.2024.0262","usgsCitation":"Berl, R.E., Fisk, J.J., van Eeden, L.M., Salerno, J., Fernández-Llamazares, Á., Leong, K., Long, J.W., Boomer, G.S., Williams, C.K., Arbieu, U., Lehnen, L., Landon, A., Ellis, E.C., Verschuuren, B., Larson, L., and Gavin, M.C., 2025, Foundational principles of an applied cultural evolutionary science for natural resource management and conservation: Philosophical Transactions of the Royal Society B Biological Sciences, v. 380, no. 1940, 20240262, 18 p., https://doi.org/10.1098/rstb.2024.0262.","productDescription":"20240262, 18 p.","ipdsId":"IP-176724","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":497405,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rstb.2024.0262","text":"Publisher Index Page"},{"id":497202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"380","issue":"1940","noUsgsAuthors":false,"publicationDate":"2025-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Berl, Richard Eugene Waggaman 0000-0002-4154-1319","orcid":"https://orcid.org/0000-0002-4154-1319","contributorId":336851,"corporation":false,"usgs":true,"family":"Berl","given":"Richard","email":"","middleInitial":"Eugene Waggaman","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":951653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisk, Jonathan J.","contributorId":193004,"corporation":false,"usgs":false,"family":"Fisk","given":"Jonathan","middleInitial":"J.","affiliations":[],"preferred":false,"id":951654,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Eeden, Lily M.","contributorId":356303,"corporation":false,"usgs":false,"family":"van Eeden","given":"Lily","middleInitial":"M.","affiliations":[{"id":84952,"text":"Arthur Rylah Institute for Environmental Research, Department of Energy, Environment and Climate Action, State Government of Victoria, Australia; Applied Chemistry and Environmental Sciences, STEM College, RMIT University, Australia","active":true,"usgs":false}],"preferred":false,"id":951655,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Salerno, Jonathan","contributorId":336855,"corporation":false,"usgs":false,"family":"Salerno","given":"Jonathan","email":"","affiliations":[{"id":80889,"text":"Department of Human Dimensions of Natural Resources, Graduate Degree Program in Ecology, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":951656,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fernández-Llamazares, Álvaro","contributorId":356305,"corporation":false,"usgs":false,"family":"Fernández-Llamazares","given":"Álvaro","affiliations":[{"id":84953,"text":"Institut de Ciència i Tecnologia Ambientals (ICTA-UAB) and Department of Animal Biology, Plant Biology and Ecology (BABVE), Universitat Autònoma de Barcelona, Barcelona Spain","active":true,"usgs":false}],"preferred":false,"id":951657,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leong, Kirsten","contributorId":207317,"corporation":false,"usgs":false,"family":"Leong","given":"Kirsten","affiliations":[{"id":37520,"text":"NOAA Fisheries, Pacific Islands Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":951658,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Long, Jonathan W.","contributorId":329818,"corporation":false,"usgs":false,"family":"Long","given":"Jonathan","email":"","middleInitial":"W.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":951659,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boomer, G. 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However, not including end-users, especially decision-makers representing communities vulnerable to climate change, can limit model utility, increase epistemic risks, and lead to information misuse in decision-making. While the ESM community increasingly values broad community engagement, end-users may not initially perceive models as useful for local planning. Co-designing models with end-users fosters two-way learning: users better understand models and their outputs, while modelers gain insights into fine-scale local processes like monitoring practices and management priorities. Higher-level co-design can lead to more customized, priority-driven, and useful modeling products. Despite these benefits, modelers often struggle to initiate meaningful partnerships with local communities. Therefore, this paper explores model co-design from the perspective of modelers. This study presents two case studies where modelers and social scientists collaborated with Indigenous communities' decision-makers to reflect their priorities in model design and application. In the Arctic Rivers Project, high-resolution climate and hydrology data sets for Alaska were developed with guidance from an Indigenous Advisory Council, using optimized, coupled land-atmosphere models. In the Mid-Klamath Project, we partnered with the Karuk Tribe's Department of Natural Resources to assess climate change and prescribed burning impacts on terrestrial hydrology in the Klamath River Basin. Drawing from these studies, we introduce a four-level framework: (a) Co-design Configuration; (b) Model Tuning; (c) Incorporate Contextual Knowledge; (d) Co-develop New Model Functions. We aim to help researchers consider and compare co-design across diverse modeling projects systematically and coherently.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025AV001921","usgsCitation":"Cheng, Y., Herman-Mercer, N.M., Newman, A.J., Musselman, K., Woelfle-Hazard, C., Blaskey, D., Brooks, C.M., Carlson, T., Koch, J.C., Morrison, M., Mutter, E., Sarna-Wojcicki, D., Thomas, P., Tlen, J., and Toohey, R.C., 2025, Toward co-designed Earth System Models: Reflecting end-user priorities in local applications from a modeler's perspective: AGU Advances, v. 6, no. 6, e2025AV001921, 22 p., https://doi.org/10.1029/2025AV001921.","productDescription":"e2025AV001921, 22 p.","ipdsId":"IP-180103","costCenters":[{"id":41166,"text":"Southwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":497389,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025av001921","text":"Publisher Index Page"},{"id":497138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, California, Oregon","otherGeospatial":"Klamath River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.81342926294906,\n 43.10561588671308\n ],\n [\n -124.48040635076697,\n 43.10561588671308\n ],\n [\n -124.48040635076697,\n 40.206104446782575\n ],\n [\n -120.81342926294906,\n 40.206104446782575\n ],\n [\n -120.81342926294906,\n 43.10561588671308\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -134.3515714377868,\n 54.21401982837219\n ],\n [\n -129.6567253884985,\n 55.448838662658915\n ],\n [\n -135.22819993126652,\n 59.90471003527469\n ],\n [\n -137.5718554227408,\n 59.27306781866508\n ],\n [\n -140.1719287726436,\n 60.887401823457054\n ],\n [\n -141.29803380842512,\n 70.13465386032021\n ],\n [\n -159.35092543271705,\n 71.93980230779283\n ],\n [\n -168.77768266130207,\n 66.4070220804696\n ],\n [\n -173.27479921730367,\n 63.087644787979826\n ],\n [\n -170.49847785815396,\n 54.72140652436224\n ],\n [\n -179.22972703122795,\n 52.19095364355289\n ],\n [\n -179.15904264949774,\n 50.99859454461824\n ],\n [\n -167.48667021150578,\n 52.360855523237205\n ],\n [\n -152.11412379152463,\n 56.65675207331881\n ],\n [\n -145.63785436419175,\n 58.89837720034234\n ],\n [\n -138.264490234756,\n 58.22681850225416\n ],\n [\n -134.3515714377868,\n 54.21401982837219\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Cheng, Yifan","contributorId":332342,"corporation":false,"usgs":false,"family":"Cheng","given":"Yifan","email":"","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":951377,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herman-Mercer, Nicole M. 0000-0001-5933-4978 nhmercer@usgs.gov","orcid":"https://orcid.org/0000-0001-5933-4978","contributorId":3927,"corporation":false,"usgs":true,"family":"Herman-Mercer","given":"Nicole","email":"nhmercer@usgs.gov","middleInitial":"M.","affiliations":[{"id":438,"text":"National Research Program - 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2025 - Ultramafic float rocks at Jezero crater (Mars): Excavation of lower crustal rocks or mantle peridotites by impact cratering?","interactions":[],"lastModifiedDate":"2025-12-09T14:49:58.02368","indexId":"70272807","displayToPublicDate":"2025-12-04T07:44:11","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Ultramafic float rocks at Jezero crater (Mars): Excavation of lower crustal rocks or mantle peridotites by impact cratering?","docAbstract":"Based on observation and data from meteorites and in situ scientific missions, experiments as well as models, the Martian mantle is assumed to share some compositional and mineralogical affinity with the terrestrial mantle. However, there might be subtle differences like the Martian mantle being more ferroan. Yet, we do not have any direct analysis of a Martian mantle rock to confirm this assumption. NASA’s Perseverance rover found olivine-rich boulder-sized float rocks on the upper Jezero fan (Mars). These boulders have an ultramafic composition and their mineralogy is dominantly composed of Fo73±3 olivine with high-Mg orthopyroxene, Cr-rich Ti-Fe oxides and minor plagioclase and high-Ca pyroxene. Microtextural and petrological analysis reveals that these minerals crystallized at equilibrium. In addition, these boulders are different from all the bedrocks analyzed by Perseverance along its traverse which are crustal igneous rocks and sediments. Comparing our data to Martian meteorites and available Mars bulk silicate models (BSM), we discuss that these boulders could represent primitive melts and/or lower crustal material, and we specifically hypothesize that they could be mantle peridotites. We propose that these putative mantle rocks could have been excavated by the succession of impacts from the shallow mantle or lower crust in the Isidis region where Jezero crater is located. These olivine-rich boulders could thereby constitute the first direct analysis of a Martian mantle rock.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2025.119746","usgsCitation":"Beyssac, O., Clave, E., Forni, O., Udry, A., Pascuzzo, A., Dehouck, E., Beck, P., Mandon, L., Quantin-Nataf, C., Mangold, N., Lopez-Reyes, G., Royer, C., Gasnault, O., Gabriel, T.S., Kah, L., Schroder, S., Johnson, J., Bertrand, T., Chide, B., Fouchet, T., Simon, J., Montmessin, F., Fau, A., Maurice, S., Wiens, R., and Cousin, A., 2025, Ultramafic float rocks at Jezero crater (Mars): Excavation of lower crustal rocks or mantle peridotites by impact cratering?: Earth and Planetary Science Letters, v. 675, 119746, 14 p., https://doi.org/10.1016/j.epsl.2025.119746.","productDescription":"119746, 14 p.","ipdsId":"IP-182722","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":497407,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2025.119746","text":"Publisher Index Page"},{"id":497275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"675","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Beyssac, O.","contributorId":290034,"corporation":false,"usgs":false,"family":"Beyssac","given":"O.","affiliations":[{"id":62313,"text":"Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, CNRS, Sorbonne Université","active":true,"usgs":false}],"preferred":false,"id":951826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clave, E.","contributorId":296842,"corporation":false,"usgs":false,"family":"Clave","given":"E.","affiliations":[{"id":64188,"text":"Planetary Exploration Team, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":951827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forni, O.","contributorId":290037,"corporation":false,"usgs":false,"family":"Forni","given":"O.","affiliations":[{"id":62314,"text":"Institut de Recherche en Astrophysique et Planétologie, Université de Toulouse","active":true,"usgs":false}],"preferred":false,"id":951828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Udry, A.","contributorId":290128,"corporation":false,"usgs":false,"family":"Udry","given":"A.","affiliations":[],"preferred":false,"id":951829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pascuzzo, A.C.","contributorId":363588,"corporation":false,"usgs":false,"family":"Pascuzzo","given":"A.C.","affiliations":[{"id":86727,"text":"Department of Earth, Environmental, Planetary Science, Brown University","active":true,"usgs":false}],"preferred":false,"id":951830,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dehouck, E.","contributorId":290073,"corporation":false,"usgs":false,"family":"Dehouck","given":"E.","affiliations":[{"id":62330,"text":"Univ. 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CNES","active":true,"usgs":false}],"preferred":false,"id":951849,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Wiens, R.C.","contributorId":344463,"corporation":false,"usgs":false,"family":"Wiens","given":"R.C.","email":"","affiliations":[{"id":82350,"text":"Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, USA","active":true,"usgs":false}],"preferred":false,"id":951850,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Cousin, A.","contributorId":290035,"corporation":false,"usgs":false,"family":"Cousin","given":"A.","affiliations":[{"id":62314,"text":"Institut de Recherche en Astrophysique et Planétologie, Université de Toulouse","active":true,"usgs":false}],"preferred":false,"id":951851,"contributorType":{"id":1,"text":"Authors"},"rank":26}]}} ,{"id":70272635,"text":"sir20255087 - 2025 - Simulation of groundwater flow in Wake County, North Carolina, 2000 through 2070","interactions":[],"lastModifiedDate":"2026-02-03T16:44:17.27377","indexId":"sir20255087","displayToPublicDate":"2025-12-03T15:00:16","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5087","displayTitle":"Simulation of Groundwater Flow in Wake County, North Carolina, 2000 Through 2070","title":"Simulation of groundwater flow in Wake County, North Carolina, 2000 through 2070","docAbstract":"In 2019, the U.S. Geological Survey and Wake County Environmental Services began a collaborative study to evaluate groundwater resources and long-term groundwater availability in the county’s fractured-rock groundwater system. Wake County, in central North Carolina, is experiencing rapid population growth, associated land development, and changing water use. Hydrogeologic data including groundwater levels, aquifer testing, borehole fracture flow measurements, water-quality samples, and groundwater age-dating tracers were collected, along with findings from previous investigations, to help inform a conceptual model of the flow system used to develop a modular three-dimensional finite-difference groundwater-flow model (MODFLOW) for simulating historical and future groundwater conditions from 2000 to 2070.
Hydraulic conductivity and transmissivity ranges were estimated from 17 slug tests and 21 borehole-flow measurements. Groundwater-quality analytical results from 19 sampling sites indicate that oxidation-reduction (redox) conditions varied within the regolith and bedrock and that minimal evaporation occurred before recharge entered the groundwater system. Age dating revealed mixtures of older and younger water, ranging from the 1940s to the 1990s—indicating variable flow pathways of recharge within permeable bedrock fracture zones.
To simplify the complex fractured-rock groundwater system, two layers representing the regolith and the fractured bedrock were used in the MODFLOW model. Model calibration included parameter estimation and provided a reasonable fit to observed groundwater levels and estimated stream base flows. The model forecast scenarios incorporated future climate-model data for two emissions scenarios with land cover change projections to simulate potential impacts to future groundwater levels, recharge, and base flows. Recharge and base flow projections were largely within historical ranges, with no apparent long-term trends, but did indicate a slight downward shift in median values—likely, in part, because of differences in spatial resolution of input climate datasets. Seasonal patterns were consistent with historical data, with projections of possible increases in future winter recharge. Model limitations are discussed, and additional monitoring and model refinement needs are highlighted to support decision making for local groundwater management.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255087","issn":"2328-0328","collaboration":"Prepared in cooperation with Wake County Environmental Services","usgsCitation":"Antolino, D.J., Gonthier, G.J., and Sanchez, G.M., 2025, Simulation of groundwater flow in Wake County, North Carolina, 2000 through 2070: U.S. Geological Survey Scientific Investigations Report 2025–5087, 77 p., https://doi.org/10.3133/sir20255087.","productDescription":"Report: xii, 77 p.; 2 Data Releases","numberOfPages":"94","onlineOnly":"Y","ipdsId":"IP-141136","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":497806,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119050.htm"},{"id":496949,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5087/coverthb.jpg"},{"id":497076,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255087/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5087 HTML"},{"id":497075,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5087/sir20255087.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5087 XML"},{"id":496956,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UC8F3Z","text":"USGS Data Release","linkHelpText":"- Water-level data and results for slug tests performed in 17 wells in Wake County, North Carolina, 2020 and 2021"},{"id":496955,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N3EQ86","text":"USGS Data Release","linkHelpText":"- MODFLOW-NWT model used to simulate groundwater flow in Wake County, North Carolina, 2000 through 2070"},{"id":496950,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5087/sir20255087.pdf","size":"21.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5087 PDF"},{"id":496958,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5087/images"}],"country":"United States","state":"North Carolina","county":"Wake County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-78.5465,36.0218],[-78.4307,35.9795],[-78.3969,35.9387],[-78.3567,35.9318],[-78.351,35.909],[-78.3385,35.9052],[-78.3347,35.8997],[-78.3302,35.896],[-78.3245,35.896],[-78.3177,35.8963],[-78.3137,35.8976],[-78.3081,35.8935],[-78.2948,35.8797],[-78.292,35.8792],[-78.2893,35.8741],[-78.2859,35.8713],[-78.2831,35.8681],[-78.2782,35.8631],[-78.2749,35.8567],[-78.2756,35.8494],[-78.2707,35.843],[-78.2657,35.8361],[-78.2652,35.8325],[-78.2613,35.8315],[-78.2591,35.826],[-78.2599,35.8183],[-78.3731,35.7523],[-78.4635,35.7072],[-78.4686,35.7087],[-78.4709,35.7078],[-78.4732,35.7046],[-78.4778,35.7011],[-78.5716,35.6255],[-78.708,35.5191],[-78.9196,35.5857],[-78.9956,35.6104],[-78.9796,35.6656],[-78.9439,35.7515],[-78.9421,35.756],[-78.9403,35.7615],[-78.9337,35.7859],[-78.9191,35.8216],[-78.9096,35.8506],[-78.9076,35.8678],[-78.89,35.8676],[-78.8298,35.8689],[-78.8056,35.9281],[-78.7609,35.9176],[-78.751,35.9307],[-78.7372,35.941],[-78.714,35.9729],[-78.7009,36.0068],[-78.6985,36.0131],[-78.7048,36.0091],[-78.7077,36.0087],[-78.7076,36.0132],[-78.7052,36.0223],[-78.7085,36.0287],[-78.7102,36.0287],[-78.713,36.0278],[-78.7164,36.0283],[-78.7232,36.0334],[-78.726,36.0343],[-78.7272,36.0334],[-78.7278,36.0289],[-78.7324,36.0267],[-78.7353,36.0199],[-78.7422,36.0209],[-78.75,36.026],[-78.7551,36.0283],[-78.7545,36.0301],[-78.7511,36.0323],[-78.7499,36.035],[-78.747,36.0395],[-78.7492,36.0427],[-78.7503,36.0468],[-78.7519,36.0491],[-78.7564,36.0532],[-78.7498,36.0718],[-78.7088,36.0768],[-78.6895,36.0752],[-78.5922,36.0378],[-78.5465,36.0218]]]},\"properties\":{\"name\":\"Wake\",\"state\":\"NC\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, suite 500
Norcross, GA 30093
Contact Us- USGS Publications Warehouse
","tableOfContents":"Habitat degradation has been associated with the loss of many self-sustaining Muskellunge Esox masquinongy populations, including those in Green Bay, where stocking has provided an exceptional trophy fishery but restoration goals include establishing self-sustaining populations and there is little evidence of natural recruitment. Our objectives were to determine whether (1) Muskellunge spawning locations and occurrence of successful hatching were related to a suite of habitat characteristics, (2) proportions of Muskellunge spawning in or outside of tributaries to lower Green Bay were different, and (3) Muskellunge showed spawning site fidelity.
From 2017 to 2019, adult Muskellunge (N = 60) were surgically implanted with radio and acoustic transmitters to identify spawning locations, where we measured a suite of habitat variables and attempted to collect eggs and larvae. Side-scan sonar was used to quantify the amount of habitat available to Muskellunge for egg deposition in the Fox and Menominee rivers, which are tributaries to Green Bay.
Muskellunge eggs were collected at 58 locations, but only two larvae were collected from a single location. Bottom slope, depth, distance to shore, gravel substrate, organic matter, and dissolved oxygen best predicted the presence of Muskellunge eggs. We determined that little habitat associated with Muskellunge egg deposition was available in the Fox and Menominee rivers. However, approximately half of tagged Muskellunge appeared to spawn outside of tributaries. Muskellunge in Green Bay displayed moderate spawning site fidelity.
Our results suggest that successful hatching occurs at very low levels and the lack of suitable Muskellunge spawning habitat in Green Bay tributaries may be limiting natural reproduction. Changes in spatial allocation of stocked fish and enhancement of known spawning locations may increase egg deposition and subsequent natural reproduction.
Bank erosion in Arctic rivers helps shape channel geometry, mobilizes carbon from permafrost and influences sediment delivery to the Arctic Ocean. On Alaska's Arctic coastal plain, rivers begin flowing during snowmelt in late spring while extensive river ice persists in channels, such that hydraulics are altered and water is kept cool. The effects of river ice on permafrost bank erosion are poorly understood, primarily due to a dearth of field observations and a lack of river ice in existing models.
To address this knowledge gap, we developed a numerical model to simulate the melt of substrate interstitial ice and bank collapse along individual permafrost river banks. We parameterize the model with field observations from riverbanks in three different channels on the Canning River delta, which are disparately impacted by river ice during snowmelt. We explore the bank erosion produced without river ice in the model and with modern river ice model scenarios that we drive with different stages and water temperature boundary conditions. We also compare predicted erosion rates to observations from satellite imagery to validate this approach.
In the model, banks are idealized as vertical profiles that rise 1–2 m above the river bed and are comprised of silt- to sand-sized sediment with dense roots in the active layer. Underneath, we generalize bank ice content underneath the active layer to represent ice-rich permafrost on the river corridor boundaries. The model predicts that these ice-rich river banks can erode by 2–6 m/yr. Scenarios without ice underpredict erosion in the distributary channels. Scenarios with varying river ice for different deltaic channels produce erosion rates similar to observations.
Our results suggest that the prolonged melt of thick river ice in a delta nonlinearly impacts permafrost bank erosion by blocking river discharge to certain branches, heightening stage across the distributary network and locally limiting river water warming. Given expected changes in air temperature and hydrology, future estimates of Arctic river bank erosion could be improved by considering river ice.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.70189","usgsCitation":"Arcuri, J., Overeem, I., Repasch, M., Anderson, R.S., Anderson, S.P., Koch, J.C., and Urban, F., 2025, River ice controls permafrost bank erosion across an Arctic delta: Earth Surface Processes and Landforms, v. 50, no. 15, e70189, 16 p., https://doi.org/10.1002/esp.70189.","productDescription":"e70189, 16 p.","ipdsId":"IP-179882","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":497140,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Canning River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -144.96629304307663,\n 70.01100341463973\n ],\n [\n -146.12712314576996,\n 70.21006797383902\n ],\n [\n -146.58932980728264,\n 69.87830435250464\n ],\n [\n -146.27585557894227,\n 68.96347382420646\n ],\n [\n -145.52140711630287,\n 68.61915114052712\n ],\n [\n -144.96629304307663,\n 70.01100341463973\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"50","issue":"15","noUsgsAuthors":false,"publicationDate":"2025-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Arcuri, J","contributorId":363264,"corporation":false,"usgs":false,"family":"Arcuri","given":"J","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":951392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Overeem, Irina","contributorId":197487,"corporation":false,"usgs":false,"family":"Overeem","given":"Irina","email":"","affiliations":[],"preferred":false,"id":951393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Repasch, Marisa 0000-0003-2636-9896","orcid":"https://orcid.org/0000-0003-2636-9896","contributorId":334190,"corporation":false,"usgs":false,"family":"Repasch","given":"Marisa","email":"","affiliations":[],"preferred":false,"id":951394,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, R. S.","contributorId":269710,"corporation":false,"usgs":false,"family":"Anderson","given":"R.","middleInitial":"S.","affiliations":[],"preferred":false,"id":951395,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, S. P.","contributorId":363265,"corporation":false,"usgs":false,"family":"Anderson","given":"S.","middleInitial":"P.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":951396,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":951397,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Urban, Frank 0000-0002-1329-1703 furban@usgs.gov","orcid":"https://orcid.org/0000-0002-1329-1703","contributorId":127827,"corporation":false,"usgs":true,"family":"Urban","given":"Frank","email":"furban@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":951398,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70272673,"text":"70272673 - 2025 - Present and future coastal flooding hazard for Long Island, NY and Long Island Sound (NY/CT), USA","interactions":[],"lastModifiedDate":"2025-12-03T16:09:30.659734","indexId":"70272673","displayToPublicDate":"2025-12-02T10:03:43","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Present and future coastal flooding hazard for Long Island, NY and Long Island Sound (NY/CT), USA","docAbstract":"Coastal flooding and the associated damages due to storms are increasing with sea level rise around the world, with regional variability in the severity of impacts., Researchers and resource managers need to better understand and predict the future shifts in coastal flooding due to these processes to plan for resilient and sustainable communities. Here we present an analysis of long-term historical records of water levels, tides, and modeled present-day wave climatologies, to characterize the present-day inundation extent in Long Island Sound and Long Island, NY. To understand the potential future changes in inundation extent, we provide a similar analysis of future climate projections of non-tidal residuals (storm surge) for the year 2050 and compare these projections with our present-day results. We examine both the magnitude of relatively frequent events with a 0.99 annual exceedance probability to more extreme events with a 0.01 annual exceedance probability (or the 1 in 100-year event). This range of events is relevant for local managers to understand the spatial variability in coastal inundation, in addition to planning for larger more catastrophic events.
","language":"English","publisher":"EarthArXiv","doi":"10.31223/X5117Q","usgsCitation":"Cook, S.E., and Herdman, L.M., 2025, Present and future coastal flooding hazard for Long Island, NY and Long Island Sound (NY/CT), USA: EarthArXiv, https://doi.org/10.31223/X5117Q.","productDescription":"39 p.","ipdsId":"IP-170004","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":497010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cook, Salme Ellen 0000-0003-1129-6209","orcid":"https://orcid.org/0000-0003-1129-6209","contributorId":303775,"corporation":false,"usgs":true,"family":"Cook","given":"Salme","email":"","middleInitial":"Ellen","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herdman, Liv M. 0000-0002-5444-6441 lherdman@usgs.gov","orcid":"https://orcid.org/0000-0002-5444-6441","contributorId":149964,"corporation":false,"usgs":true,"family":"Herdman","given":"Liv","email":"lherdman@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951282,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70272733,"text":"70272733 - 2025 - Projecting management-relevant change of undeveloped coastal barriers with the Mesoscale Explicit Ecogeomorphic Barrier model (MEEB) v1.0","interactions":[],"lastModifiedDate":"2025-12-05T16:02:59.966789","indexId":"70272733","displayToPublicDate":"2025-12-02T09:59:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"Projecting management-relevant change of undeveloped coastal barriers with the Mesoscale Explicit Ecogeomorphic Barrier model (MEEB) v1.0","docAbstract":"Models of coastal barrier geomorphic and ecologic change are valuable tools for understanding and predicting when, where, and how barriers evolve and transition between ecogeomorphic states. Few existing models of barrier systems are designed to operate over spatiotemporal scales congruous with effective management practices (i.e., decades/kilometers, referred to herein as “mesoscales”), incorporate important ecogeomorphic feedbacks, and provide probabilistic projections of future change. Here, we present a new numerical model designed to address these gaps by explicitly yet efficiently simulating coupled aeolian, marine, vegetation, and shoreline components of barrier evolution over spatiotemporal scales relevant to management. The Mesoscale Explicit Ecogeomorphic Barrier model (MEEB) simulates subaerial ecomorphologic change of undeveloped barrier systems over kilometers and decades using meter-scale spatial resolution and weekly time steps. MEEB applies simplified parameterizations to represent and couple key ecogeomorphic processes: dune growth, vegetation expansion and mortality, beach and foredune erosion, barrier overwash, and shoreline and shoreface change. The model is parameterized and calibrated with observed elevation, vegetation, and water level data for a case study site of North Core Banks, NC, USA. Simulated ecogeomorphic change in model hindcasts agrees well with observations, demonstrating both favorable skill scores and qualitatively correct behavior. We also describe an additional model framework for producing probabilistic projections that account for uncertainties related to future forcing conditions and intrinsic stochastic dynamics and demonstrate the probabilistic framework's utility with example forecast simulations. As a mesoscale model, MEEB is designed to investigate questions about future barrier ecogeomorphic change of moderate complexity, offering semi-qualitative predictions and semi-quantitative explanations. For example, MEEB can be used to investigate how climate-induced shifts in ecological composition may alter the likelihood of morphologic impacts or to generate probabilistic projections of ecogeomorphic state change.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/gmd-18-9319-2025","usgsCitation":"Reeves, I.R., Ashton, A.D., Lentz, E.E., Sherwood, C.R., Passeri, D., and Zeigler, S., 2025, Projecting management-relevant change of undeveloped coastal barriers with the Mesoscale Explicit Ecogeomorphic Barrier model (MEEB) v1.0: Geoscientific Model Development, v. 18, p. 9319-9348, https://doi.org/10.5194/gmd-18-9319-2025.","productDescription":"30 p.","startPage":"9319","endPage":"9348","ipdsId":"IP-170312","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":497392,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-18-9319-2025","text":"Publisher Index Page"},{"id":497142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","noUsgsAuthors":false,"publicationDate":"2025-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Reeves, Ian Robert 0000-0002-6675-3756","orcid":"https://orcid.org/0000-0002-6675-3756","contributorId":363346,"corporation":false,"usgs":true,"family":"Reeves","given":"Ian","middleInitial":"Robert","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashton, Andrew D. 0000-0002-0241-3090","orcid":"https://orcid.org/0000-0002-0241-3090","contributorId":363347,"corporation":false,"usgs":false,"family":"Ashton","given":"Andrew","middleInitial":"D.","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":951467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lentz, Erika E. 0000-0002-0621-8954 elentz@usgs.gov","orcid":"https://orcid.org/0000-0002-0621-8954","contributorId":173964,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika","email":"elentz@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951469,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Passeri, Davina 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951470,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zeigler, Sara 0000-0002-5472-769X","orcid":"https://orcid.org/0000-0002-5472-769X","contributorId":222703,"corporation":false,"usgs":true,"family":"Zeigler","given":"Sara","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951471,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274180,"text":"70274180 - 2025 - Aeromagnetic and magnetotelluric imaging of west-central Idaho and the Stibnite-Yellow Pine mining district: A regional to district perspective","interactions":[],"lastModifiedDate":"2026-03-04T22:38:45.947857","indexId":"70274180","displayToPublicDate":"2025-12-01T15:30:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Aeromagnetic and magnetotelluric imaging of west-central Idaho and the Stibnite-Yellow Pine mining district: A regional to district perspective","docAbstract":"Aeromagnetic and magnetotelluric (MT) data are used to better understand the geology and mineral resources near the Stibnite-Yellow Pine mining district in central Idaho. The reduced-to-pole (RTP) transformation of regional-scale aeromagnetic data shows that allochthonous island-arc rocks west of the Salmon River suture are significantly more magnetic than the Laurentian continental rocks east of the suture and that the granitoids of the Idaho batholith have moderate to low magnetization in both early, metaluminous, and late, peraluminous phases. Application of tilt derivative to aeromagnetic data highlights major crustal-scale structures. The 5-km upward continued magnetic data indicate island-arc rocks have deep magnetic sources. The 110-km-long MT profile images resistivity structure to depths around 30 km. At shallow depths, resistivity corresponds to mapped geologic units, with moderate resistivities underlying volcanic and roof-pendant metasedimentary rocks and moderate to high resistivities occurring beneath the Idaho batholith. Crustal-scale moderate resistivities beneath the suture image the results of tectonomagmatic processes that accompanied suturing and translating allochthonous terranes. Low resistivity values beneath and fringing the batholith are derived from metasedimentary rocks that may have served as a melt source and reductant during melt generation and provided metals during later ore formation.
In the Stibnite-Yellow Pine mining district, a high-resolution aeromagnetic compilation is shown to correlate with mapped lithologies and mineral deposit-related structures. The RTP transform distinguishes magnetic and nonmagnetic granitoid phases of the Idaho batholith. The tilt derivative highlights metasedimentary rocks, some of which are favorable ore hosts. The Meadow Creek fault hosts the Stibnite and Hangar Flats deposits and is imaged as a magnetic low due to hydrothermal alteration. Reconstructions of magnetic anomaly offsets and orebodies indicate around 3 km of post-95 Ma dextral separation, with some or all of the offset inferred to postdate the main Au mineralization episode (61–66 Ma).
","language":"English","publisher":"GeoScienceWorld","doi":"10.5382/econgeo.5182","usgsCitation":"Anderson, E., Rodriguez, B.D., Lund, K., Dail, C., and Breen, B., 2025, Aeromagnetic and magnetotelluric imaging of west-central Idaho and the Stibnite-Yellow Pine mining district: A regional to district perspective: Economic Geology, v. 120, no. 8, p. 1899-1923, https://doi.org/10.5382/econgeo.5182.","productDescription":"26 p.","startPage":"1899","endPage":"1923","ipdsId":"IP-114615","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":500851,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5382/econgeo.5182","text":"Publisher Index Page"},{"id":500769,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"west-central Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.63626406020117,\n 44.307766155511956\n ],\n [\n -115.63626406020117,\n 43.87879267849277\n ],\n [\n -114.41828968668513,\n 43.87879267849277\n ],\n [\n -114.41828968668513,\n 44.307766155511956\n ],\n [\n -115.63626406020117,\n 44.307766155511956\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"120","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Eric D. 0000-0002-0138-6166","orcid":"https://orcid.org/0000-0002-0138-6166","contributorId":202072,"corporation":false,"usgs":true,"family":"Anderson","given":"Eric D.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":956794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rodriguez, Brian D. 0000-0002-2263-611X brod@usgs.gov","orcid":"https://orcid.org/0000-0002-2263-611X","contributorId":836,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Brian","email":"brod@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":956795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lund, Karen 0000-0002-4249-3582 klund@usgs.gov","orcid":"https://orcid.org/0000-0002-4249-3582","contributorId":1235,"corporation":false,"usgs":true,"family":"Lund","given":"Karen","email":"klund@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":956796,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dail, Christopher","contributorId":367119,"corporation":false,"usgs":false,"family":"Dail","given":"Christopher","affiliations":[{"id":87550,"text":"Midas Gold Idaho, Donnelly, ID 83615","active":true,"usgs":false}],"preferred":false,"id":956797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Breen, Bill","contributorId":367120,"corporation":false,"usgs":false,"family":"Breen","given":"Bill","affiliations":[{"id":87551,"text":"Independent Consultant, Hope, Idaho 83836","active":true,"usgs":false}],"preferred":false,"id":956798,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273917,"text":"70273917 - 2025 - Geologic models underpinning the 2024 U.S. Geological Survey assessment of undiscovered oil and gas resources in the Hosston and Travis Peak Formations of the onshore Gulf Coast region, U.S.A.","interactions":[],"lastModifiedDate":"2026-02-17T21:07:05.234713","indexId":"70273917","displayToPublicDate":"2025-12-01T11:42:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1717,"text":"GCAGS Journal","active":true,"publicationSubtype":{"id":10}},"title":"Geologic models underpinning the 2024 U.S. Geological Survey assessment of undiscovered oil and gas resources in the Hosston and Travis Peak Formations of the onshore Gulf Coast region, U.S.A.","docAbstract":"The Early Cretaceous (Berriasian–Hauterivian) Hosston Formation in Louisiana and eastward is time correlative to the Travis Peak Formation of Texas and southern Arkansas. The formation is a first-order clastic sequence with a regional carbonate transgressive surface as an upper contact. The Hosston and Travis Peak formations contain conventional natural gas and oil accumulations that have been produced for nearly a century. These mature reservoirs contain terrigenous fluvial-deltaic, shore-zone, and paralic deposits across the productive trend; organic-lean mudstone and siltstone lithologies are found outboard of the Lower Cretaceous shelf margin. Producing reservoirs exhibit normal pressure gradients from 0.43 to 0.55 psi/ft (9.7 to 12.4 kpa/m), depths from 4000 to over 20,000 ft (1220 to 6100 m), and temperatures from 150 to 385°F (65 to 196°C). Wells are primarily vertical completions. The number of new field wildcats has been declining since the late 1990s. This paper presents comprehensive geologic models, which include lithofacies maps, structure and isopach maps, burial history models, regional seismic interpretations, and events charts that underpin the recently completed U.S. Geological Survey assessment of undiscovered, technically recoverable hydrocarbons within the Hosston and Travis Peak formations. This study also provides geographic and stratigraphic distributions of Hosston–Travis Peak reservoir properties, including geopressure, reservoir temperature, porosity, permeability, API gravity, and gas-oil ratios. Results indicate estimated undiscovered, technically recoverable mean resources of 28 million barrels of oil and 35.8 trillion cubic ft of gas in conventional and continuous accumulations within the Lower Cretaceous Hosston and Travis Peak formations of the onshore U.S. Gulf Coast region. Quantitative assessment results are detailed in U.S. Geological Survey Fact Sheet 2025–3021 and associated Data Release.","language":"English","publisher":"Gulf Coast Association of Geological Societies","doi":"10.62371/STWR8033","usgsCitation":"Burke, L.A., Paxton, S.T., Kinney, S.A., Gianoutsos, N.J., Dubiel, R., and Pitman, J., 2025, Geologic models underpinning the 2024 U.S. Geological Survey assessment of undiscovered oil and gas resources in the Hosston and Travis Peak Formations of the onshore Gulf Coast region, U.S.A.: GCAGS Journal, v. 14, p. 87-105, https://doi.org/10.62371/STWR8033.","productDescription":"19 p.","startPage":"87","endPage":"105","ipdsId":"IP-171733","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":500123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":500094,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://gcags.org/Journal/2025_V14/2025_GCAGS_Journal_v14_07_p87-105_Burke_Et_Al.html"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -104.06103212694106,\n 38.66590683410158\n ],\n [\n -104.06103212694106,\n 24.0496145009851\n ],\n [\n -78.58542051058421,\n 24.0496145009851\n ],\n [\n -78.58542051058421,\n 38.66590683410158\n ],\n [\n -104.06103212694106,\n 38.66590683410158\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burke, Lauri A. 0000-0002-2035-8048 lburke@usgs.gov","orcid":"https://orcid.org/0000-0002-2035-8048","contributorId":3859,"corporation":false,"usgs":true,"family":"Burke","given":"Lauri","email":"lburke@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":955755,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paxton, Stanley T. 0000-0002-9098-1740 spaxton@usgs.gov","orcid":"https://orcid.org/0000-0002-9098-1740","contributorId":739,"corporation":false,"usgs":true,"family":"Paxton","given":"Stanley","email":"spaxton@usgs.gov","middleInitial":"T.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":955756,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinney, Scott A. 0000-0001-5008-5813 skinney@usgs.gov","orcid":"https://orcid.org/0000-0001-5008-5813","contributorId":1395,"corporation":false,"usgs":true,"family":"Kinney","given":"Scott","email":"skinney@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":955757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gianoutsos, Nicholas J. 0000-0002-6510-6549 ngianoutsos@usgs.gov","orcid":"https://orcid.org/0000-0002-6510-6549","contributorId":3607,"corporation":false,"usgs":true,"family":"Gianoutsos","given":"Nicholas","email":"ngianoutsos@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":955758,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dubiel, Russell F. 0000-0002-1280-0350","orcid":"https://orcid.org/0000-0002-1280-0350","contributorId":214101,"corporation":false,"usgs":true,"family":"Dubiel","given":"Russell F.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":955759,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pitman, Janet K. 0000-0002-0441-779X","orcid":"https://orcid.org/0000-0002-0441-779X","contributorId":228982,"corporation":false,"usgs":true,"family":"Pitman","given":"Janet K.","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":955760,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}